diff --git a/src/core/handlers/step11_map_handler.py b/src/core/handlers/step11_map_handler.py
index d3a43c6..a8c7180 100644
--- a/src/core/handlers/step11_map_handler.py
+++ b/src/core/handlers/step11_map_handler.py
@@ -243,32 +243,79 @@ class Step11MapHandler(BaseStepHandler):
                 context.notify('step11_map', 'warning',
                               f'共享上下文预计算失败: {e}，回退逐个处理')
 
-        # ── 顺序生成（避免 Windows spawn 下 ProcessPoolExecutor 死锁）──
-        # 局部 Kriging 内部已做 16 块顺序分块，每块 ~20-30s，
-        # 每张图约 5-8 分钟。64 张 ≈ 5-8 小时，但进度完全透明可见。
+        # ── 并发生成 ──
+        # 克里金插值内部为 numpy/scipy 运算（释放 GIL），
+        # 使用 ThreadPoolExecutor 并发处理多个 CSV，大幅缩短总耗时。
+        # 注意：不使用 ProcessPoolExecutor（Windows spawn 会导致死锁）。
+        _max_workers = int(config.get('kriging_workers', 2))
+        _max_workers = max(1, min(_max_workers, total, os.cpu_count() or 4))
+
         generated: List[str] = []
         errors: Dict[str, str] = {}
 
-        context.notify('step11_map', 'info',
-                       f'顺序生成 {total} 张专题图（局部 Kriging 自适应分块）')
-
-        for idx, csv_p in enumerate(csv_paths):
-            percent = int(idx / total * 100)
-            context.notify('step11_map', 'info',
-                          f'专题图 [{idx+1}/{total}]: {Path(csv_p).name}')
-
-            global_event_bus.publish('ProgressUpdate', {
-                'percentage': percent,
-                'message': f'Step11: {idx+1}/{total} {Path(csv_p).stem}',
-            })
-
+        if _max_workers > 1 and total > 1:
+            # ★ 主线程预先设置 matplotlib Agg 后端（避免多线程竞争）
+            import matplotlib
             try:
-                result_path, _ = _process_one_map(csv_p, base_kwargs, output_dir)
-                generated.append(result_path)
-            except Exception as e:
-                errors[csv_p] = str(e)
-                context.notify('step11_map', 'warning',
-                              f'专题图 FAIL: {Path(csv_p).name} — {e}')
+                matplotlib.use('Agg', force=True)
+            except Exception:
+                pass
+
+            import concurrent.futures
+            context.notify('step11_map', 'info',
+                           f'并发生成 {total} 张专题图（{_max_workers} 线程并行）')
+
+            completed = 0
+            with concurrent.futures.ThreadPoolExecutor(
+                    max_workers=_max_workers) as executor:
+                future_map = {
+                    executor.submit(
+                        _process_one_map, csv_p, base_kwargs, output_dir
+                    ): csv_p
+                    for csv_p in csv_paths
+                }
+                for future in concurrent.futures.as_completed(future_map):
+                    csv_p = future_map[future]
+                    completed += 1
+                    try:
+                        result_path, _ = future.result()
+                        generated.append(result_path)
+                        context.notify('step11_map', 'info',
+                                       f'专题图 [{completed}/{total}] ✓: '
+                                       f'{Path(csv_p).name}')
+                    except Exception as e:
+                        errors[csv_p] = str(e)
+                        context.notify('step11_map', 'warning',
+                                       f'专题图 [{completed}/{total}] ✗: '
+                                       f'{Path(csv_p).name} — {e}')
+
+                    percent = int(completed / total * 100)
+                    global_event_bus.publish('ProgressUpdate', {
+                        'percentage': percent,
+                        'message': f'Step11: {completed}/{total} '
+                                   f'{Path(csv_p).stem}',
+                    })
+        else:
+            context.notify('step11_map', 'info',
+                           f'顺序生成 {total} 张专题图（局部 Kriging 自适应分块）')
+
+            for idx, csv_p in enumerate(csv_paths):
+                percent = int(idx / total * 100)
+                context.notify('step11_map', 'info',
+                              f'专题图 [{idx+1}/{total}]: {Path(csv_p).name}')
+
+                global_event_bus.publish('ProgressUpdate', {
+                    'percentage': percent,
+                    'message': f'Step11: {idx+1}/{total} {Path(csv_p).stem}',
+                })
+
+                try:
+                    result_path, _ = _process_one_map(csv_p, base_kwargs, output_dir)
+                    generated.append(result_path)
+                except Exception as e:
+                    errors[csv_p] = str(e)
+                    context.notify('step11_map', 'warning',
+                                  f'专题图 FAIL: {Path(csv_p).name} — {e}')
 
         step_end_time = time.time()
         elapsed = step_end_time - step_start_time